With growing consumerization of apps, the ubiquitous nature of the cloud and mobile, and the Internet of Things, organizations are being confronted with rising volumes of applications and data. ‘Information Chaos’ is how AIIM refers to this phenomena that has IT scrambling to control mounting...
Intelligent Document Recognition (IDR) is one type of technology being employed to increase productivity and reduce costs
To utilize OCR and ICR technologies, most organizations rely on a deeper capture application, often referred to as IDR (Intelligent Document Recognition). IDR is the business rules and workflow engine around OCR and ICR that provides needed context about a document (identification, classification, separation), and invokes the appropriate OCR or ICR technology to process a job. This type of data capture and analysis software is used for a variety of purposes, such as transactions, business intelligence, applications, claim forms and customer support. Document recognition technologies such as OCR and ICR can automatically extract information that is essential to business intelligence and strategy
The use of Intelligent Document Recognition (IDR) technology has delivered significant cost savings in relation to minimizing and/or eliminating human touch and involvement throughout the capture process
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So this year, we celebrated ten successful years of developing knowledge management solutions and providing document recognition, data capture and linguistic software
This is done manually or automatically, using IDR (intelligent document recognition) and OCR...But it almost always implies that you should not start with sophisticated OCR and intelligent document recognition, complex workflows, and complex reporting
Your first job is to start using document recognition technology, your second, is to make it as accurate as possible
Try Intelligent document recognition (IDR) -- cautiously Chaining together different recognitions into a cascade is often used for intelligent document recognition (IDR) to sort the documents into document classes, thus eliminating that part of prep work
Improvements in automatic image enhancement and semi-structured document recognition technology have reduced the AP man-power needed, but still you are dealing with documents being prepared by others
There is software that cleans up images so that document recognition technology has the best fighting chance at accuracy, there is also software makes scanned images look as if they originated digitally
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